v0.1.0 — tracing, replay, evals, and governance for agent runs

First complete reference implementation.

What's in it

Runtime substrate

• Deterministic scripted agent runtime; policy gating (allow / deny / needs_review) evaluated before every step
• Digest-addressed JSONL traces; replay engine with per-field divergence detection (catches code drift, environment drift, and tampering)
• Golden-task eval harness gating CI on every commit

Governance objects (field-aligned with wutai & stillmirror-review — see docs/object-model-alignment.md)

• PolicyDecision, RiskSignal, ReviewerSeat as first-class data
• Attestations: scoped ratification by a named human (declared_scope / excluded_scope, proposed_by ≠ attested_by), consuming recorded review debt
• Run-level trust verdict (trusted / review_required / blocked), per-run coverage declarations

Observability

• OTel spans with digests and policy verdicts as attributes; Prometheus metrics incl. aro_review_debt_total and aro_attestations_total
• Pre-provisioned Grafana dashboard (screenshot in README, captured live)
• SLOs incl. two governance SLOs (docs/slo.md), full error taxonomy (docs/error-taxonomy.md)

Infra

• Postgres store with FOR UPDATE SKIP LOCKED queue claims (SQLite fallback); worker retry with exponential backoff, dead-lettering, deterministic chaos injection; API rate limiting
• docker-compose stack (api, worker, Postgres, Prometheus, Grafana) with healthchecks — verified end to end; optional k8s manifests
• CI: lint, unit, integration, Postgres service-container job, golden replay regression, web build

Surfaces: FastAPI (runs / traces / replay / attestations / queue / metrics), queue worker, React + Vite dashboard.

62 files of Python across five workspace packages, 49 tests, benchmark numbers measured not asserted (docs/benchmark.md).